code: def fbeta_score(precision, recall, beta=1.0):
      beta_square = beta * beta
      return (
          (1 + beta_square)
          * precision
          * recall
          / (beta_square * precision + recall)
      )
  
file_path: chainer/tests/chainer_tests/functions_tests/evaluation_tests/test_classification_summary.py
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import functions
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 3 for calling a global function with example usage: fbeta_score(precision, recall, beta) and returns: unknown